TY - JOUR
T1 - Dynamic Cloud Deployment of a MapReduce Architecture
AU - Loughran, Steve
AU - Alcaraz Calero, Jose M.
AU - Farrell, Andrew
AU - Kirschnick, Johannes
AU - Guijarro, Julio
PY - 2012/11/1
Y1 - 2012/11/1
N2 - Cloud-based Map Reduce services process large datasets in the cloud, significantly reducing users' infrastructure requirements. Almost all of these services are cloud-vendor-specific and thus internally designed within their own cloud infrastructures, resulting in two important limitations. First, cloud vendors don't let developers see and evaluate how the Map Reduce architecture is managed internally. Second, users can't build their own private cloud-infrastructure-based offerings or use different public cloud infrastructures for deploying Map Reduce services. The authors' proposed framework enables the dynamic deployment of a Map Reduce service in virtual infrastructures from either public or private cloud providers.
AB - Cloud-based Map Reduce services process large datasets in the cloud, significantly reducing users' infrastructure requirements. Almost all of these services are cloud-vendor-specific and thus internally designed within their own cloud infrastructures, resulting in two important limitations. First, cloud vendors don't let developers see and evaluate how the Map Reduce architecture is managed internally. Second, users can't build their own private cloud-infrastructure-based offerings or use different public cloud infrastructures for deploying Map Reduce services. The authors' proposed framework enables the dynamic deployment of a Map Reduce service in virtual infrastructures from either public or private cloud providers.
UR - https://ieeexplore.ieee.org/document/6109213
U2 - 10.1109/MIC.2011.163
DO - 10.1109/MIC.2011.163
M3 - Article
SN - 1089-7801
VL - 16
SP - 40
EP - 50
JO - IEEE Internet Computing
JF - IEEE Internet Computing
IS - 6
ER -